1. Field of the Invention
The present invention relates generally to a Multiple Input Multiple Output (MIMO) system, and in particular, to a partial iterative detection and decoding apparatus and method in a MIMO system.
2. Description of the Related Art
Due to the rapid growth of mobile communication markets, various multimedia services for wireless environment are under high demand. In order to provide the multimedia services, a large capacity of Transmit (TX) data and a high speed of data transfer are in progress. Therefore, it is most important to develop methods for efficiently using the limited frequencies in the wireless communication systems. To do so, wireless communication systems require new transfer techniques using multiple antennas.
One of the new transfer techniques is a MIMO system that uses multiple antennas at a transmitter and a receiver. Compared with a system using a single antenna, this MIMO system can increase channel capacity in proportion to the number of antennas without additional frequency or transmission power allocation.
MIMO technologies are classified into a spatial diversity scheme, a spatial multiplexing scheme, and a combination scheme of spatial diversity and spatial multiplexing. The spatial diversity scheme can obtain a diversity gain corresponding to a product of the number of TX and Receive (RX) antennas, improving transmission reliability. The spatial multiplexing scheme can increase the data rate by simultaneously transmitting a plurality of data streams.
When the spatial multiplexing scheme is used in the MIMO system, mutual interference occurs between the transmitted data streams. Therefore, the receiver detects signals using a Maximum Likelihood (ML) considering the influence of interference signal, or detects signals after interference cancellation. Examples of the interference cancellation scheme include Zero Forcing (ZF) and Minimum Mean Square Error (MMSE).
However, the ML receiver has a drawback in that the complexity increases in proportion to a square of the number of TX antennas and the length of a codeword. Therefore, research on reception algorithms has been conducted to reduce the calculation complexity of the receiver and obtain the performance close to that of the ML receiver.
In addition, the MIMO system uses an Iterative Detection and Decoding (IDD) scheme in which a turbo principle is applied to a MIMO receiver. In the MIMO IDD scheme, a single coder is concatenated with a channel coder and a MIMO coder. Thus, a MIMO detector of the MIMO receiver detects a signal received through an antenna and outputs the detection signal to a channel decoder. The channel decoder improves a bit performance by decoding the detection signal output from the MIMO detector and feeds back the decoded signal to the MIMO detector. The MIMO detector again generates a detection signal using the feedback signal. The MIMO receiver iteratively performs the above-described procedures. Examples of the MIMO IDD scheme include a list MIMO scheme and a turbo blast scheme. The two schemes have the same IDD scheme as the spatial multiplexing scheme of the transmitter, but are different in terms of the detection of the MIMO signal.
FIG. 1 is a diagram of a conventional MIMO IDD receiver.
Referring to FIG. 1, when a signal is received, a MIMO detector 101 detects the received signal and generates a first soft decision data to a channel decoder 105. The soft decision data indicates a Log Likelihood Ratio (LLR).
The channel decoder 105 decodes each bit using the first soft decision data as priori information and calculates a second soft decision value. That is, the channel decoder 105 corrects an error by decoding the first soft decision data.
The second soft decision value calculated by the channel decoder 105 is fed back to the MIMO detector 101 and is used as the priori information for the IDD. By repeating these procedures, the reliability of the received bits can be improved.
The MIMO IDD scheme recalculates the soft decision value by performing the IDD of the soft decision value calculated from the separated detector and decoder, thereby improving the performance of the MIMO system. However, because the IDD scheme calculates as many LLRs as the size of the coding blocks of the detector and decoder in each iteration, the complexity of the system increases as a total number of iterations increases.